Familial hypercholesterolaemia (FH) patients have elevated levels of low-density lipoprotein cholesterol, rendering them at high risk of premature coronary artery disease (PCAD). However, the FH prevalence among angiogram-proven PCAD (AP-PCAD) patients and their status of coronary risk factors (CRFs) have not been reported in the Asian population.This study aimed to (1) determine the prevalence of clinically diagnosed FH among AP-PCAD patients, (2) compare CRFs between AP-PCAD patients with control groups, and (3) identify the independent predictors of PCAD.AP-PCAD patients and FH patients without PCAD were recruited from Cardiology and Specialist Lipid Clinics. Subjects were divided into AP-PCAD with FH (G1), AP-PCAD without FH (G2), FH without PCAD (G3) and normal controls (G4). Medical records were collected from the clinic database and standardised questionnaires. FH was clinically diagnosed using Dutch Lipid Clinic Network Criteria.±SD age: 55.6±8.5years). The prevalence of Definite, Potential and All FH among AP-PCAD patients were 6%(19/319), 16% (51/319) and 45.5% (145/319) respectively. G1 had higher central obesity, family history of PCAD and family history of hypercholesterolaemia compared to other groups. Among all subjects, diabetes [OR(95% CI): 4.7], hypertension [OR(95% CI): 14.1], FH [OR(95% CI): 2.9] and Potential (Definite and Probable) FH [OR(95% CI): 4.5] were independent predictors for PCAD. Among FH patients, family history of PCAD [OR(95% CI): 3.0] and Definite FH [OR(95% CI): 7.1] were independent predictors for PCAD.A total of 572 subjects were recruited (males:86.4%; meanPotential FH is common among AP-PCAD patients and contributes greatly to the AP-PCAD. FH-PCAD subjects have greater proportions of various risk factors compared to other groups. Presence of FH, diabetes, hypertension, obesity and family history of PCAD are independent predictors of PCAD. FH with PCAD is in very-high-risk category, hence, early management of modifiable CRFs in these patients are warranted. LDLR). Familial hypercholesterolaemia causes elevated low-density lipoprotein cholesterol (LDL-C) and total cholesterol (TC) serum levels resulting in increased risk of coronary artery disease (CAD)  prior to commencement of the study. The study was conducted in accordance with the Declaration of Helsinki. All subjects provided written informed consent prior to enrolment into the study.Fig 1).Out of 319 AP-PCAD patients in this study (G1 and G2), the prevalence of clinically diagnosed Definite FH and Probable FH was 6% (19/319) and 10% (32/319), respectively, which add up into 16% Potential FH. When Possible FH was included on top of Potential FH, All FH was 45.5% (145/319). Almost 30% of the AP-PCAD patients (94/319) were Possible FH and 54.5% (174/319) were Unlikely FH  has higher proportions of obesity (BMI) compared to G3 and G4. The presence of family history of PCAD was also significantly higher in G1 compared to the other groups (p<0.05). Similarly, there was also a significantly high percentage of individuals with family history of HC in G1 compared to G2, G3 and G4 (p<0.05).TC levels of G1 was significantly higher compared to G2 but significantly lower compared to G3. Pre-treatment LDL-C levels of G1 was significantly higher than G2 and G4, but similar to G3, whom were also FH individuals. Only four patients (3.7%) were presented with TX and 15 patients (13.8%) with corneal arcus in G1. Only one individual (2.0%) presented with TX and 42 individuals (82.4%) with corneal arcus in G3 .Fig 2 shows that after HC (98.1%) and male gender (85.3%), obesity was the most common risk factor among this cohort with (77.0%) followed by hypertension (76.5%) and diabetes (51.1%).Individuals with PCAD from G1 (n = 145) and G2 (n = 174) were combined to determine the most common risk factors among PCAD individuals. Table 2). All risk factors including lipid profiles were analysed for simple logistic regression. Patients without available data were excluded from the analysis. Further multiple logistic regression analysis shows that only FH, Potential and Probable FH, hypertension, diabetes and family history of HC were significantly associated with PCAD among all individuals in the study (p<0.05).The factors associated with PCAD among all groups in the study was determined using logistic regression analysis (Table 3). All risk factors and lipid profiles were analysed using simple logistic regression. Further multiple logistic regression analysis shows that only Definite FH, hypertension, diabetes mellitus and family history of PCAD were significant risk factors for PCAD among those with FH (p<0.05).Subjects of G1 (n = 145) and G3 (n = 101) was combined (n = 246) to identify the risk factors associated with PCAD among FH individuals using logistic regression (Table 4). Due to small data, not all risk factors were able to run through regression analysis. Therefore, only available risk factors were analysed using simple logistic regression. Further multiple logistic regression analysis shows that only obesity and family history of PCAD were significant risk factors for PCAD among Potential FH (p<0.05).Those with Potential FH  from G1 and G3 was combined to identify the risk factors associated with PCAD among Potential FH using logistic regression (Table 5(A). Overall, hypertension and diabetes were the greatest independent risk factors that contributed to development PCAD , followed by clinically diagnosed as FH and Potential FH .The risk factors that were shown to significantly associated with PCAD were re-analysed using the same regression method. The remaining risk factors were then tested for their interactions and all the factors were re-analysed for the final prediction model of PCAD among all individuals in the study Table 5(B). Results show that FH patients with diabetes have 6.4 times the odds to develop PCAD compared to those without diabetes. Hypertensive patients were 3.6 times more likely to develop PCAD compared to FH patients without hypertension. Besides, those with family history of PCAD have almost 3.0 times the odds to develop PCAD compared to those without family history of PCAD. Those with Definite FH category have 7.1 times the odds to develop PCAD compared to those who were Probable and Possible FH.The final prediction model of PCAD among individuals with FH were shown in Table 5(C). Results show that Potential FH patients with family history of PCAD have 6.7 times the odds to develop PCAD compared to those who were not Potential FH. Besides, patients who were obese were 15.4 times more likely to develop PCAD compared to FH patients who were not obese.The final prediction model of PCAD among individuals with Potential FH were shown in This study is the first to describe the prevalence of clinically diagnosed FH among PCAD cohort in Malaysia, where the prevalence of 16.0% Potential FH is far higher than in the normal population, which had been reported to be about 1% . FH is gCurrently, the majority of Malaysian FH patients are not genetically confirmed, where genetic testing itself is still not a standard protocol for FH confirmation in the majority of the Asian countries, including Malaysia . NeverthTo the best of our knowledge, this study is also the first report on the prevalence of FH among angiogram-proven PCAD patients in Southeast Asia, although similar studies, also using DLCC criteria had been previously reported in other regions. While the overall prevalence of FH in this present study is relatively high (45.5%), several studies ,35 had jThe prevalence of FH were discovered in lower frequency in several studies, such as a recent study conducted in the United States reported that clinical FH was present in just about 1 out of 10 patients with PCAD  , In contIn contrast, a Spanish study reported a much higher prevalence of clinically diagnosed FH among patients with ACS at 77.6%; although with a similar 1:2 ratio between Potential and Possible FH  . This isTo date, FH among PCAD patients in hospital settings are still under-diagnosed –42. HoweCoronary artery disease is a major concern worldwide and CVD is the leading cause of death . ConventIn this present study, the level of TC among those with FH-PCAD was significantly lower than G3 (FH without CAD). This could be explained by the fact that most individuals with PCAD were already treated with medications for CAD and statin therapy for at least 3 months prior to the data collection.There was no positive association between smoking status and type of groups in this present study. The regression analysis of factors associated with CAD also showed that smoking was not associated with PCAD, in contrast with other previous studies –47. Howes age, gender, smoking, hypertension, diabetes mellitus, family history of CAD, personal history of CAD, HDL-C, TG, small dense LDLs, and lipoprotein(a) [Lp(a)] levels have been studied and reported as potential predictors of atherosclerotic burden and/or CVD prognosis among individuals with FH Reviewers' comments:Reviewer's Responses to Questions  Comments to the Author1. Is the manuscript technically sound, and do the data support the conclusions?  The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: PartlyReviewer #2: Yes**********  2. Has the statistical analysis been performed appropriately and rigorously?   Reviewer #1: YesReviewer #2: Yes**********  3. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.  The Reviewer #1: NoReviewer #2: Yes**********  4. Is the manuscript presented in an intelligible fashion and written in standard English?  PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: Yes**********  5. Review Comments to the Author  Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: Nawawi et al. conducted a comparative cross-sectional study to examine the prevalence of familial hypercholesterolemia (FH) among angiogram-proven premature CAD (PCAD) patients, the distribution of coronary risk factors, and the prediction of PCAD by the risk factors in Malaysia. The major findings showed that hypertension [OR (95% CI): 14.1 ] and diabetes [OR (95% CI): 4.7 ] carry much more risk than FH [OR (95% CI): 2.9 ] to predict PCAD. However, such an interpretation needs cautions. Other findings add minimal information to current knowledge regarding FH in PCAD, when lacing genetic analysis.Major critiques:1. The importance of possible FH is overemphasized. From the analysis of table 5, the odds ratio for potential FH (definite FH + probable FH) is 4.5, and that for FH (definite FH + probable FH + possible FH) is 2.9. This indicates that possible FH is of minimal clinical significance for predicting PCAD. The author should analyze the odds ratio of possible HF, and if it is the case, the part of possible FH should be toned down in the full paper, including the abstract.2. The definition of premature CAD (PCAD) in this study is age of onset: males: <55; females: <60 years. However, in Table 1, the age range of Group 3 (+FH/-PCAD) is 42 – 74 years and that for Group 4 (–FH/-PCAD) is 46 – 72 years. The age distribution cannot exclude that some male patients younger than 55 years and female patients younger than 60 years may develop PCAD later in their life and should not grouped as -PCAD.Other comments1. The definition of PCAD in this study is age of onset: males: <55; females: <60 years. However, in Table 1, the age range of Group 1 (+FH/+PCAD) is 26 – 76 years and that for Group (–FH/+PCAD) is 35 – 75 years. In this case, presence of cardiovascular risk factors should be before the diagnosis of the CAD to be the risk factors. The authors need to clarify the time sequence of appearance of risk factors and onset of PCAD.2. Similarly, in Figure 2, regarding the percentage of ex-smoker and current smokers, do you count it at the entry of this study, or at the onset of PCAD?3. In Group 2, 97.7% of patients were given lipid-lowering drugs, however, the difference of LDL-C values between pre-treatment and post-treatment is 0.4 mmol/L, are the data correct? Because 97.2% of patients in Group 1 were on lipid-lowering drugs and the difference of LDL-C values between pre-treatment and post-treatment is 1.8 mmol/L.Reviewer #2: Review PONE-D-21-27710Title: Familial Hypercholesterolaemia and coronary risk factors among patients with angiogram-proven premature coronary artery disease in an Asian cohortAuthors: Nazli SA, Chua Y-A, Kasim NAM et alBackground - This paper reports the prevalence of clinically diagnosed FH in Malaysian patients with and without angiographically proven premature coronary artery disease (AP-PCAD) and, in a four-way analysis, assesses the prevalence of coronary risk factors (CRFs) in subjects with and without AP-PCAD by FH status. It concludes by reporting the results of a multiple logistic regression analysis to determine the association between CRFs and CAD in the total study population and separately for those with FH.Diagnostic criteria - A particular strength of this large study of 572 subjects is its rigorous evaluation of CAD defined as a previous medical history of an abnormal coronary angiogram with stenosis >50% in at least one major epicardial coronary artery or prior PCI and/or CABG in males with an age of onset <55 & females <60 years. FH was diagnosed using the Dutch Lipid Clinic Network criteria (DLCNC), although the authors accept the lack of confirmatory genetic testing for FH-causing mutations is a limitation. Nevertheless, arguably excessive credence is given in the paper to the DLCNC as a basis for a clinical diagnosis of FH. The criteria were initially developed as a means of cost-effectively maximising detection rates for cascade testing programmes by screening only relatives of index patients at high likelihood of genetic FH based on their DLNC score. Identification of an elevated LDL-cholesterol levels in 1st and 2nd-degree relatives would then confirm the likelihood of FH in the index case as well as identifying previously undiagnosed and untreated relatives. As fast-throughput, less expensive, methods of mutation testing became available, DLCN criteria scores have increasingly been used to select patients warranting confirmatory genetic testing. Detection of an FH-causing mutation then initiates cascade testing for that mutation.Misclassification with DLCN scores - FH mutation detection rates in patients assessed by DLCN scoring has been documented in a number of studies . The former study included cascade-screened patients and those with Achilles tendon thickness measurements, which may have resulted in a positive diagnostic selection bias, whereas the latter smaller study recruited patients sequentially attending a lipid clinic over a three-year period so there may be less risk of bias. The results are summarised below:---------------------------------------------------------------------------------------------Tada H et al Futema M et alDLCN score n Mutation n MutationDiagnosis positive (%) positive (%)----------------------------------------------------------------------------------------------Unlikely <3 367 5 (1) 13 3 (23)Possible 3-5 156 49 (31) 69 19 (28)Probable 6-8 57 30 (53) 49 19 (39)Definite. >8 100 91 (91) 89 48 (54)----------------------------------------------------------------------------------------------Clearly nearly all patients with a score of <3 will not have an FH-causing mutation and over two thirds with a “possible” score of 3-5 will also be unaffected. A mutation will be identified in only about a half with a “probable” score of 6-8, but the majority with a “definite” score of >8 will have an FH-causing mutation. This suggests that the authors’ conclusion in the abstract that “almost half of the AP-PCAD patients with a score of >3 should be classified as “clinically diagnosed FH” is misleading, particularly since “possible FH” (score 3-5) accounted for 65% (94/145) of all patients categorised as having “clinically diagnosed FH”. In fact, their data shows that only 19/319 (6.0%) have a “definite” score >8 indicating a high likelihood of an FH-causing mutation being identified. They might alternatively consider concluding that 16% have “potential” FH (i.e. DLCN score >6) which suggests that about half of such patients may actually have a mutation. However, it is clearly misleading to conclude in the abstract that the prevalence of FH among AP-PCAD patients is 45.5%. This figure should be relegated to the results section of the paper and removed from the abstract. I accept it is appropriate to consider the finding in relation to the existing literature in the discussion, but it is inappropriate to give it such prominence in the abstract.Results – These are clearly presented both graphically and in tabular form. In Figure 1, to avoid any confusion, it would be helpful to state in the title that the prevalence of FH is based on the DLCN criteria.The high prevalence (Table 1) of diabetes in patients with PCAD with and without FH defined by a DLCN score >3 (44% & 57% DM respectively) is striking. Diabetes is, of course, well recognised to result in premature cardiovascular disease. A clinical history of premature CAD scores 2 in the DLCN criteria and patients with premature cerebral or peripheral vascular disease score 1. Consequently, any patient with both premature CAD and cerebrovascular disease will score 3 and be classified as “possible FH” regardless of their LDL cholesterol concentration.Unfortunately, the presentation of the results at present does not allow the reader to assess whether a diagnosis of diabetes is inflating the DLCN estimate of FH. Although type 2 diabetes is usually associated with raised triglyceride levels, low HDL, and with little or no increase in total and LDL cholesterol, nevertheless, given the mean age of the population studied, it would not be surprising to find that many of the PCAD subjects with diabetes had modestly increased pre-treatment LDL concentrations of >4.0 – 4.9 mmol/l, which would result in a DLCN score of 3 for subjects with PCAD even in the absence of any other clinical criteria indicative of FH. Perhaps the lipid profiles for these patients could be added as a supplementary table using the same format as Table 1? It would be particularly helpful to view the triglyceride concentrations since individuals with the lowest TG level (0.4-1.0 mmol/l) were shown to have the highest mutation detection rate (60%) in the study by Marta et al. (op cit) and decreased to 20% in those in the top quartile (2.16-4.3 mmol/l). Consequently, in the Welsh Cascade Screening Programme, a DLCN score is reduced by 2 points for a fasting TG of 2.5-3.5, and more for higher TG concentrationsTables 2 & 3 depict clearly the factors associated with PCAD in a logistic regression analysis. I would suggest adding to the title of Table 3 with “clinically diagnosed FH with DLCN score >3 and, similarly, for Table 4 add “with a DLCN score >6”. Table 5 very succinctly summarises the findings of the final prediction model. Again, I would be inclined to include the DLNC scores.Specific points:Line 60: The prevalence cited of ~1 in 100 is almost high enough to suggest a “founder effect” but the reference is to a secondary source. Could the authors please cite the primary source?Line 90: It might be helpful to cite a reference for Malaysia having the lowest mean age of onset for PCAD.Line 117: Inclusion criteria – presumably both type 1 & 2 patients with diabetes were eligible for inclusion? The tables do not provide these data, but it is possible that this information was not available.Line 125: A total of 572 patients were recruited to the study. Do the authors know how many patients were eligible, the number approached to participate and the participation rate?Line 129: The inclusion criteria for AP-PCAD are clearly defined, but the criteria for Non-PCAD “controls” do not appear to be specified. Had the “controls” undergone angiography and been shown to have no evidence of stenosis or was this established by questionnaire? It is important to clarify this.Line 132: Were lipids and lipoproteins measured centrally or by multiple methods locally at hospitals/clinics that referred patients to the National Heart Institute and Specialist Clinics. Were triglyceride measurements fasting? It might be helpful to be rather more specific about the sampling frame from which patients were recruited.Line 133: Presumably LDL-C concentrations were calculated using the Friedewald formula?Line 202: The abbreviation CA for corneal arcus is not commonly used. Was it used earlier in the paper?References – Reference 24 duplicates number 21Discussion – The discussion is well written and clearly expressed. I wonder, however, whether it would benefit by shortening? I could not find a word count but my impression is the paper probably exceeds 5,000 words after excluding the references. If the discussion was less discursive, it would probably be more impactful – and it deserves to be.Lines 262-270 start by justifiably focusing on the main findings and the strengths of the study. Nevertheless, I think it is a mistake to assert, as the headline finding, that the prevalence of FH was 45.5% among AP-PCAD patients. Instead, I suggest using as a surrogate for “clinically diagnosed FH” a DLCN score of either >6 [probable + definite FH termed “potential” FH in the paper] or >8 [“definite”- approximating to a genetically confirmed diagnosis]. Including patients with a score of 3-5 [“possible”] introduces diagnostic misclassification and results in over-interpretation of the findings and an unconvincing prevalence estimate of 45.5%. Using this obviously fallible definition undermines the credibility of the study’s findings.Lines 271-277. Most health care systems do not have access to routine genetic testing for FH. Perhaps one sentence might suffice for this paragraph.Lines 278-287. This paragraph places the findings in the context of the existing literature and is important. The next paragraph (lines 288-299) suggests that the detection rate of potential FH (score >6) is higher in patients with AP-PCAD, or those who have undergone revascularisation procedures, when compared to those with ACS without prior angiographic confirmation. Perhaps simply citing references here rather than detailing individual studies would suffice?Lines 300-320. The key fact here seems to be that in this Spanish study (ref 43) the prevalence of genetically confirmed FH in patients with PCAD was not dissimilar to that in the current study using the DLNC score for “definite FH”. A further Northern European Study (44) also reported similar consistent findings.Lines 321-328. This paragraph highlights the importance of considering the diagnosis of FH in patients with a diagnosis of PCAD in the coronary care setting and the need for referral to specialist clinics for confirmation of the diagnosis and cascade testing. Perhaps it could be somewhat shortened?The remainder of the discussion concentrates on the interesting results of the logistic regression analyses that examine the independent predictors for PCAD. These findings are consistent with previous studies. Interestingly, obesity was shown to be a significant independent predictor of PCAD in patients with potential FH (DLNC score >6). Northern European registry studies have low rates of obesity in FH patients and cannot, therefore, address this question with adequate statistical power. However, as their populations are becoming increasingly overweight and obese, this is potentially an important insight. Overall, however, the authors may feel this section of the discussion could be shortened.Before concluding, the authors consider objectively limitations of the study and, perhaps, the diagnostic misclassification associated particularly with lower DLCN FH scores should be added.Summary – This is an interesting study that extends existing knowledge by assessing the prevalence of clinically diagnosed FH in Malaysian patients with and without premature coronary artery disease. The categorisation of cases was rigorously defined angiographically, but it is not clear whether unaffected patients had undergone angiography with no evidence of stenosis found or whether this was elicited by questionnaire. FH was defined clinically using the Dutch Lipid Clinic Network score which inevitably, in the absence of mutation testing, results in some diagnostic misclassification. This is most marked in the lowest DLCN diagnostic category of “possible FH” with a score of 3-5 in which no FH-causing mutation will be found in over two thirds of patients. It is therefore very misleading to conclude in the abstract that the prevalence of FH among AP-PCAD is 45.5% based on a score of >3 since “possible” FH accounted for 65% of patients with “clinically diagnosed FH”. The multiple logistic regression analysis results are convincing and interesting findings. Overall, the impact of the paper would arguably be strengthened if the discussion was substantially shortened.**********  6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.If you choose “no”, your identity will remain anonymous but your review may still be made public.Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.  Reviewer #1: NoYes: Professor H.Andrew W. NeilReviewer #2: https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool,  28 Apr 2022Thank you very much for the kind and constructive questions and comments. We really appreciate the consideration and attention. Below are our answers to the reviewers:# We have shortened the group’s name in the manuscript from Group 1 to G1, Group 2 to G2, Group 3 to G3 and Group 4 to G4.Reviewer 1:Comment:Nawawi et al. conducted a comparative cross-sectional study to examine the prevalence of familial hypercholesterolemia (FH) among angiogram-proven premature CAD (PCAD) patients, the distribution of coronary risk factors, and the prediction of PCAD by the risk factors in Malaysia. The major findings showed that hypertension [OR (95%CI): 14.1 ] and diabetes [OR (95% CI): 4.7 ] carry much more risk than FH [OR (95% CI): 2.9 ] to predict PCAD. However, such an interpretation needs cautions. Other findings add minimal information to current knowledge regarding FH in PCAD, when lacing genetic analysis. Response:Some studies had demonstrated that hypertension and diabetes can be a much greater independent risk for coronary artery disease even when compared with lipid biomarkers such as LDL-C level , which is supposedly the main indicator of FH. However, we agree to tone down the finding of hypertension and diabetes by rephrasing the Result section. Reference: Chan DC, Pang J, Hooper AJ, Burnett JR, Bell DA, Bates TR, van Bockxmeer FM, Watts GF. Elevated lipoprotein (a), hypertension and renal insufficiency as predictors of coronary artery disease in patients with genetically confirmed heterozygous familial hypercholesterolemia. International journal of cardiology. 2015 Dec 15;201:633-8.Comment:The importance of possible FH is overemphasized. From the analysis of table 5, the odds ratio for potential FH (definite FH + probable FH) is 4.5, and that for FH (definite FH + probable FH + possible FH) is 2.9. This indicates that possible FH is of minimal clinical significance for predicting PCAD. The author should analyze the odds ratio of possible HF, and if it is the case, the part of possible FH should be toned down in the full paper, including the abstract. Response:The independent odds ratio for Possible FH has been calculated in Table 2 and 3, where it turns out that regardless of what is the sample cohort , the odds ratios for association of Possible FH with PCAD is <1, which means Possible FH has minimal clinical significance for predicting FH. We have toned down the prevalence of All FH by relegate it to the result section only, and further highlight the importance of Potential FH.Abstract: Page 2-3, turquoise highlight.Results: Page 10, turquoise highlight. Discussion: Page 23-24, turquoise highlight.Conclusion: Page 29, turquoise highlight. Comment:The definition of premature CAD (PCAD) in this study is age of onset: males: <55; females: <60 years. However, in Table 1, the age range of Group 3 (+FH/-PCAD) is 42 – 74 years and that for Group 4 (–FH/-PCAD) is 46 – 72 years. The age distribution cannot exclude that some male patients younger than 55 years and female patients younger than 60 years may develop PCAD later in their life and should not grouped as -PCAD. Response:The definition of PCAD used in this study was applied to patients in G1 (+FH/+PCAD) and G2 (-FH/+PCAD); in which these patients were recruited cross-sectionally based on retrospective diagnosis of CAD, and more importantly, the CAD is already developed and confirmed by angiography. For patients in G3 and G4 (-PCAD), we do not deny that the subjects may develop CAD in younger age . However, we deliberately match the age among G1, G2, G3 and G4 so their ages were not significantly different in order to ensure age-sensitive variables such as blood pressure and corneal arcus will have equal odds across the groups. Nevertheless, we have explained the possibility of recruiting patients with silent asymptomatic ischaemia in G3 & G4 in Discussion section. Comment:The definition of PCAD in this study is age of onset: males: <55; females: <60 years. However, in Table 1, the age range of Group 1 (+FH/+PCAD) is 26 – 76 years and that for Group (–FH/+PCAD) is 35 – 75 years. In this case, presence of cardiovascular risk factors should be before the diagnosis of the CAD to be the risk factors. The authors need to clarify the time sequence of appearance of risk factors and onset of PCAD. Response:The PCAD onset age is already explained the “Methodology - Study design and patient recruitment” section. Care has been taken in G1 (+FH/+PCAD) and G2 (-FH/+PCAD) where only coronary risk factors that appeared before or during the onset of PCAD were recorded. Additional phrase regarding the sequence of appearance of risk factors has been added in “Methodology - Biometric data and biological sample collection” section .Comment:Similarly, in Figure 2, regarding the percentage of ex-smoker and current smokers, do you count it at the entry of this study, or at the onset of PCAD? Response: The smoking status were specifically recorded at the onset of PCAD, which should be already sufficiently explained in the correction at “Methodology - Biometric data and biological sample collection” section.  Comment:In Group 2, 97.7% of patients were given lipid-lowering drugs, however, the difference of LDL-C values between pre-treatment and post-treatment is 0.4 mmol/L, are the data correct? Because 97.2% of patients in Group 1 were on lipid-lowering drugs and the difference of LDL-C values between pre-treatment and post-treatment is 1.8 mmol/L. Response:Yes, the data is indeed correct. The post-treatment LDL-C reduction in G1 seems greater than that in G2 because G1 is consists of FH patients, who has inherently high pre-treatment LDL-C (mean = 5.1 mmol/L) compared to the non-FH G2 (mean = 2.4 mmol/L). According to the Malaysian Clinical Practice Guidelines for Dyslipidaemia, the targeted post-treatment LDL-C for very-high coronary risk patients is 1.8 mmol/L. However, according to our preliminary data , only <10% of FH patients achieved the targeted LDL-C of 1.8 mmol/L, where large portion of patients only achieved post-treatment LDL-C of 2.6 mmol/L or greater. Non-FH hypercholesterolaemic patients may achieve better post-treatment LDL-C level where 23% of them achieved 1.8 mmol/L .This explains why the baseline LDL-C of G1 is higher compared to G2, but the post-treatment LDL-C levels of both groups were similar. Reference:1) Yung-An Chua, Sukma Azureen Nazli, Azhari Rosman, Sazzli Shahlan Kasim, Khairul Shafiq Ibrahim, Ahmad Bakhtiar Md Radzi, Noor Alicezah Mohd Kasim, Hapizah Mohd Nawawi. Prescription pattern and achievement of LDL-C targets with lipid-lowering medications among familial hypercholesterolaemia patients attending Specialist Clinics in Malaysia. The 19th International Symposium on Atherosclerosis, Kyoto, 2021. 2) Aimi Zafira Razman, Noor Alicezah Mohd Kasim, Zaliha Ismail, Alyaa Al-Khateeb and Hapizah Mohd Nawawi. Sub-optimal prescription of lipid-lowering medications and achievement of LDL-C targets in hypercholesterolaemic individuals in the community in the high and very high cardiovascular risk categories. The 19th International Symposium on Atherosclerosis, Kyoto, 2021.________________________________________________________________________________________Reviewer 2Comment:Misclassification with DLCN scores - FH mutation detection rates in patients assessed by DLCN scoring has been documented in a number of studies . The former study included cascade-screened patients and those with Achilles tendon thickness measurements, which may have resulted in a positive diagnostic selection bias, whereas the latter smaller study recruited patients sequentially attending a lipid clinic over a three-year period so there may be less risk of bias. The results are summarised below:-------------------------------------------------------Tada H et al Futema M et alDLCN score n Mutation n MutationDiagnosis positive (%) positive (%) -----------------------------------------------------FH Score Tada H et al Futema M et alUnlikely < 3 367 5 (1) 13 3 (23)Possible 3-5 156 49 (31) 69 19 (28)Probable 6-8 57 30 (53) 49 19 (39)Definite > 8 100 91 (91) 89 48 (54)---------------------------------------------------------------Clearly nearly all patients with a score of <3 will not have an FH-causing mutation and over two thirds with a “possible” score of 3-5 will also be unaffected. A mutation will be identified in only about a half with a “probable” score of 6-8, but the majority with a “definite” score of >8 will have an FH-causing mutation. This suggests that the authors’ conclusion in the abstract that “almost half of the AP-PCAD patients with a score of >3 should be classified as “clinically diagnosed FH” is misleading, particularly since “possible FH” (score 3-5) accounted for 65% (94/145) of all patients categorised as having “clinically diagnosed FH”. In fact, their data shows that only 19/319 (6.0%) have a “definite” score >8 indicating a high likelihood of an FH-causing mutation being identified. They might alternatively consider concluding that 16% have “potential” FH  which suggests that about half of such patients may actually have a mutation. However, it is clearly misleading to conclude in the abstract that the prevalence of FH among AP-PCAD patients is 45.5%. This figure should be relegated to the results section of the paper and removed from the abstract. I accept it is appropriate to consider the finding in relation to the existing literature in the discussion, but it is inappropriate to give it such prominence in the abstract.Response:We really appreciate the efforts of Reviewer 2 in thoroughly explained the quoted references for backing up his/her comment. The comment is insightful and fair.We have reduced the prominence of All FH, highlighted the prevalence of Potential FH, and concluded that Potential FH is clinically more important than All FH in the Abstract and Result sections.We also revised the Conclusion section, where the prevalence of All FH has been and replaced by mentioning Potential FH is common among Asian population.However, for comparison purpose, we still mentioned few studies which have similarly high prevalence of All FH in Discussion section. Abstract: Page 2-3, turquoise highlight.Results: Page 10, turquoise highlight. Discussion: Page 23-24, turquoise highlight.Conclusion: Page 29, turquoise highlight. Comment:Results – These are clearly presented both graphically and in tabular form. In Figure 1, to avoid any confusion, it would be helpful to state in the title that the prevalence of FH is based on the DLCN criteria. - The comment has been addressed.Comment:The high prevalence (Table 1) of diabetes in patients with PCAD with and without FH defined by a DLCN score >3 (44% & 57% DM respectively) is striking. Diabetes is, of course, well recognised to result in premature cardiovascular disease. A clinical history of premature CAD scores 2 in the DLCN criteria and patients with premature cerebral or peripheral vascular disease score 1. Consequently, any patient with both premature CAD and cerebrovascular disease will score 3 and be classified as “possible FH” regardless of their LDL cholesterol concentration. Response:In DLCN, personal premature CAD and personal peripheral vascular disease are grouped into a same group of criteria . According to the rule for counting the DLCN score, only one criterion with the highest point will be counted for the overall score . If a patient is with both premature CAD and peripheral vascular, he/she will score 2 points (premature CAD) instead of 3.In our study design, we have avoided misclassification of FH patients by only including subjects with baseline LDL-C of >4.0 mmol/L into the DLCN scoring. Those with <4.0 mmol/L were automatically classified as Unlikely FH.We have included the extra information regarding the inclusion criteria in “Methodology – Definition of Terms” section. Reference:Nordestgaard BG, Chapman MJ, Humphries SE, Ginsberg HN, Masana L, Descamps OS, Wiklund O, Hegele RA, Raal FJ, & Defesche JC. (2013). Familial hypercholesterolaemia is underdiagnosed and undertreated in the general population: guidance for clinicians to prevent coronary heart disease. European Heart Journal 34(45): 3478-3490.Comment:Unfortunately, the presentation of the results at present does not allow the reader to assess whether a diagnosis of diabetes is inflating the DLCN estimate of FH. Although type 2 diabetes is usually associated with raised triglyceride levels, low HDL, and with little or no increase in total and LDL cholesterol, nevertheless, given the mean age of the population studied, it would not be surprising to find that many of the PCAD subjects with diabetes had modestly increased pre-treatment LDL concentrations of >4.0 – 4.9 mmol/l, which would result in a DLCN score of 3 for subjects with PCAD even in the absence of any other clinical criteria indicative of FH. Perhaps the lipid profiles for these patients could be added as a supplementary table using the same format as Table 1? It would be particularly helpful to view the triglyceride concentrations since individuals with the lowest TG level (0.4-1.0 mmol/l) were shown to have the highest mutation detection rate (60%) in the study by Marta et al. (op cit) and decreased to 20% in those in the top quartile (2.16-4.3 mmol/l). Consequently, in the Welsh Cascade Screening Programme, a DLCN score is reduced by 2 points for a fasting TG of 2.5-3.5, and more for higher TG concentrations .Response:The prevalence of diabetes in Malaysia normal population was 18.3% in normal population , while in Japan, it is 12.1% , where the difference of prevalence between these two countries is about 33%.Among FH Japanese patients, the prevalence of FH in Japan to 28.6% , which means the Malaysian prevalence of diabetes among FH at 44.1% calculated (about 35% difference) in this current study is plausible.References:1. Ministry of Health Malaysia. (2020). National Health and Morbidity Survey 2019 - Non-communicable Disease: Risk Factors and other Health Problems.2. Fujii H, Funakoshi S, Maeda T, Satoh A, Kawazoe M, Ishida S, Yoshimura C, Yokota S, Tada K, Takahashi K, Ito K. Eating Speed and Incidence of Diabetes in a Japanese General Population: ISSA-CKD. Journal of Clinical Medicine. 2021 Jan;10(9):1949.3. Teramoto T, Kai T, Ozaki A, Crawford B, Arai H, & Yamashita S. (2018). Treatment patterns and lipid profile in patients with familial hypercholesterolemia in Japan. Journal of Atherosclerosis and Thrombosis 25(7): 580-592.Comment:Tables 2 & 3 depict clearly the factors associated with PCAD in a logistic regression analysis. I would suggest adding to the title of Table 3 with “clinically diagnosed FH with DLCN score >3 and, similarly, for Table 4 add “with a DLCN score >6”. Table 5 very succinctly summarises the findings of the final prediction model. Again, I would be inclined to include the DLNC scores. - The comment has been addressed, thank you very much.Comment:Line 60: The prevalence cited of ~1 in 100 is almost high enough to suggest a “founder effect” but the reference is to a secondary source. Could the authors please cite the primary source? Response:The comment has been addressed Comment:Line 90: It might be helpful to cite a reference for Malaysia having the lowest mean age of onset for PCAD. Response:The comment has been addressed. The sentence has been slightly changed. Comment:Line 117: Inclusion criteria – presumably both type 1 & 2 patients with diabetes were eligible for inclusion? The tables do not provide these data, but it is possible that this information was not available. Response:Yes, both patients with type 1 & 2 diabetes were included in the study. We have added the description in “Methodology – Definition of terms”. Comment:Line 125: A total of 572 patients were recruited to the study. Do the authors know how many patients were eligible, the number approached to participate and the participation rate?Response:For G1 (+FH/+PCAD) and G2 (-FH/+PCAD), the eligibility of patients are as below: Eligible patients, n=815The number approached, n=368Included (participation rate), n (%) : 319 (86.7)However, due to the nature of G3 (+FH/-PCAD) and G4 (+FH/-PCAD) which were recruited from convenient sampling among the community, the number of approached subjects were far numerous than what was minimally needed by the statistical analysis. Out of n=4702 non-PCAD subjects, n=253/4702 were age, ethnic and gender-matched and randomly selected for this study. Comment:Line 129: The inclusion criteria for AP-PCAD are clearly defined, but the criteria for non-PCAD “controls” do not appear to be specified. Had the “controls” undergone angiography and been shown to have no evidence of stenosis or was this established by questionnaire? It is important to clarify this. Response:Due to the study design, it was impossible to access the medical records of the controls who solely consisted of subjects recruited from community health screening programmes, where the programmes were held in municipal public halls instead of established health centres. The information on the CAD status among unaffected G3 (+FH/-PCAD) and G4 (-FH/-PCAD) were obtained by means of assisted self-reporting questionnaire without angiography confirmation. Comment:Line 132: Were lipids and lipoproteins measured centrally or by multiple methods locally at hospitals/clinics that referred patients to the National Heart Institute and Specialist Clinics. Were triglyceride measurements fasting? It might be helpful to be rather more specific about the sampling frame from which patients were recruited. Response:The lipids and lipoproteins were measured by multiple methods at each hospitals/clinics  - Yes, the triglyceride measures at fasting.Comment:Line 133: Presumably LDL-C concentrations were calculated using the Friedewald formula? Response:Yes. Calculated LDL-C derived from total cholesterol, HDL, and triglycerides levels using Friedewald formula is a standard laboratory protocol in Malaysia. We intentionally did not elaborate the details of the lipid profile analysis in order to shorten the Methodology section.Comment:Line 202: The abbreviation CA for corneal arcus is not commonly used. Was it used earlier in the paper? Response:The “CA” is not a common abbreviation. We have changed all the “CA” to “corneal arcus” in the manuscript.Comment:References – Reference 24 duplicates number 21 Response:The comment has been addressed. We have removed the duplicated reference. Comment:Discussion – The discussion is well written and clearly expressed. I wonder, however, whether it would benefit by shortening? I could not find a word count, but my impression is the paper probably exceeds 5,000 words after excluding the references. If the discussion was less discursive, it would probably be more impactful – and it deserves to be. Response:We have shortened the Discussion section slightly, thus making the word count well under 5000 words (From Introduction to Acknowledgement).Comment: Lines 262-270 start by justifiably focusing on the main findings and the strengths of the study. Nevertheless, I think it is a mistake to assert, as the headline finding, that the prevalence of FH was 45.5% among AP-PCAD patients. Instead, I suggest using as a surrogate for “clinically diagnosed FH” a DLCN score of either >6 [probable + definite FH termed “potential” FH in the paper] or >8 [“definite”- approximating to a genetically confirmed diagnosis]. Including patients with a score of 3-5 [“possible”] introduces diagnostic misclassification and results in over-interpretation of the findings and an unconvincing prevalence estimate of 45.5%. Using this obviously fallible definition undermines the credibility of the study’s findings. Response:The prevalence of FH based on All-FH has been de-emphasised in the Abstract, Results and Conclusion section.Abstract: Page 2-3, turquoise highlight.Results: Page 10, turquoise highlight. Conclusion: Page 29, turquoise highlight. Comment:Lines 271-277. Most health care systems do not have access to routine genetic testing for FH. Perhaps one sentence might suffice for this paragraph. Response:The said lines have been shortened. (Discussion: Page 23).Comment:Lines 278-287. This paragraph places the findings in the context of the existing literature and is important. The next paragraph (lines 288-299) suggests that the detection rate of potential FH (score >6) is higher in patients with AP-PCAD, or those who have undergone revascularisation procedures, when compared to those with ACS without prior angiographic confirmation. Perhaps simply citing references here rather than detailing individual studies would suffice? Response:The said lines have been shortened. Comment:Lines 321-328. This paragraph highlights the importance of considering the diagnosis of FH in patients with a diagnosis of PCAD in the coronary care setting and the need for referral to specialist clinics for confirmation of the diagnosis and cascade testing. Perhaps it could be somewhat shortened? Response:The said lines have been shortened. Comment:The remainder of the discussion concentrates on the interesting results of the logistic regression analyses that examine the independent predictors for PCAD. These findings are consistent with previous studies. Interestingly, obesity was shown to be a significant independent predictor of PCAD in patients with potential FH (DLNC score >6). Northern European registry studies have low rates of obesity in FH patients and cannot, therefore, address this question with adequate statistical power. However, as their populations are becoming increasingly overweight and obese, this is potentially an important insight. Overall, however, the authors may feel this section of the discussion could be shortened. Response:The entire paragraph starting with “coronary artery disease is a major concern worldwide…” has been slightly shortened.Comment:Before concluding, the authors consider objectively limitations of the study and, perhaps, the diagnostic misclassification associated particularly with lower DLCN FH scores should be added.Response:Since our FH subjects were all hypercholesterolaemic (baseline LDL-c <4.0 mmol/L), we are quite confident that the subjects with lower DLCN score were not caused by misinterpretation of LDL-C levels.However, we fully acknowledge that our Possible FH, which is about 2/3 of all FH patients, is relatively high in proportion and many of the Possible FH subjects may not be molecularly true FH if confirm by genetic testing.The caveat has been mentioned at the end of Discussion section. Comment:Summary – This is an interesting study that extends existing knowledge by assessing the prevalence of clinically diagnosed FH in Malaysian patients with and without premature coronary artery disease. The categorisation of cases was rigorously defined angiographically, but it is not clear whether unaffected patients had undergone angiography with no evidence of stenosis found or whether this was elicited by questionnaire. Response:As what has been answered for “Line 129” comment, we would like to clarify that the unaffected patients were assumed absent of CAD by means of assisted self-reporting questionnaire, without angiography confirmation. Comment:FH was defined clinically using the Dutch Lipid Clinic Network score which inevitably, in the absence of mutation testing, results in some diagnostic misclassification. This is most marked in the lowest DLCN diagnostic category of “possible FH” with a score of 3-5 in which no FH-causing mutation will be found in over two thirds of patients. It is therefore very misleading to conclude in the abstract that the prevalence of FH among AP-PCAD is 45.5% based on a score of >3 since “possible” FH accounted for 65% of patients with “clinically diagnosed FH”. Response:As what has been previously commented, we have changed the prevalence of FH by emphasising the Potential FH instead of All FH in the Abstract, Results and Conclusion sections.Abstract: Page 2-3, turquoise highlight.Results: Page 10, turquoise highlight. Conclusion: Page 29, turquoise highlight. Comment:The multiple logistic regression analysis results are convincing and interesting findings. Overall, the impact of the paper would arguably be strengthened if the discussion was substantially shortened.Response:We have tried our best to shorten the Discussion section. Thank you very much for all the comments.AttachmentResponse to Reviewers.docxSubmitted filename: Click here for additional data file. 25 May 2022
 PONE-D-21-27710R1

 Familial hypercholesterolaemia and coronary risk factors among patients with angiogram-proven premature coronary artery disease in an Asian cohort

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Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.  The Reviewer #1: NoReviewer #2: Yes**********  5. Is the manuscript presented in an intelligible fashion and written in standard English?  PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: Yes**********  6. Review Comments to the Author  Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: It has been a long time since the previous comments were sent . This delay in response and the substantial change of the revised manuscript makes this reviewer to read the revised manuscript from the beginning again and find some critical points.Major critiques1. This is a very unique cohort that patients with premature CAD account for more than 75% (145+174/145+174+101=76.0%) of all patients with CAD. Is this cohort representative of CAD population in your country?2. Methodology, how group 4 patients were recruited was not mentioned.3. Table 1, data of central obesity for group 2 (n = 174) are missing, which is difficult to understand.4. The patient number in Table 4 is 63, rather small, and the statistical analysis may not be appropriate.Other comments   “Subjects were divided into AP-PCAD with FH (G1)…”Abstract, 2nd sentences, “Subjects were divided into AP-CAD with FH (G1)…” �Reviewer #2: The authors have addressed my comments. However, I would very strongly recommend one change to the abstract to include the figures for Definite FH. Lines 34-36 should read "The prevalence of Definite, Potential and All FH among AP-PCAD patients were 6%(19/319), 16% (51/319) and 45.5% (145/319) respectively. It is very important to include upfront the figures for definite patients since these are consistent in findings in non-Asian studies and include patients overwhelmingly likely to have an FH-causing variant.**********  7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). 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Please note that Supporting Information files do not need this step.While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool,  29 Jun 2022Reviewer #1:1. This is a very unique cohort that patients with premature CAD account for more than 75% (145+174/145+174+101=76.0%) of all patients with CAD. Is this cohort representative of CAD population in your country?= We would like to clarify that only G1 and G2 are consist of PCAD individuals (145+174= 319). The rests in G3 and G4 (101+152= 253) are those without CAD/PCAD. Therefore, this study does not represent the proportions of PCAD among CAD cases in Malaysia. =We have added extra description in the following section to clarify the nature of G3 and G4. =Methodology - Study design and patient recruitment: .2. Methodology, how group 4 patients were recruited was not mentioned.= Those in group 3 (G3) and 4 (G4) were recruited through community health screening programmes. The methodology was briefly mentioned previously, but now we have added a new paragraph to emphasise the point.= Methodology - Study design and patient recruitment: .3. Table 1, data of central obesity for group 2 (n = 174) are missing, which is difficult to understand.= The data of central obesity for G2 (-FH/+PCAD) is missing because we did not take the measurements of waist circumference for those in this group due to the nature of recruitment for this particular group. Although the PCAD patients in G2 were consented for this study, the recruitment began way earlier than G1, G3 and G4, where the measurement of waist circumference was not part of the recruitment protocol. =For the overall analysis of regression (Results: Table 2) which involves all groups including G2 (n=572), we have no choice but to exclude central obesity. =However, we are still able to include central obesity as one of the analysis variables in regression analysis that involves FH patients in G1 and G3 (Results: Table 3 and Table 4).=Nevertheless, the absence of central obesity does not adversely affect the regression analysis and the final outcome of this study.4. The patient number in Table 4 is 63, rather small, and the statistical analysis may not be appropriate.= Based on the central limit theorem (CLT), the distribution of sample means approximates a normal distribution as the sample size gets larger, regardless of the population's distribution. Sample sizes equal to or greater than 30 are often considered sufficient for the CLT to hold . =Besides, all data for n=63 individuals were complete and variables from the univariate analysis with p value <0.25 were included in the multivariate analysis. For multivariate analysis, the value of p <0.05 were taken as significant.=Therefore, we are quite confident that our sample size for Table 4 is sufficient, and its statistical analysis is appropriate.=Reference:Mascha, E. J., & Vetter, T. R. (2018). Significance, errors, power, and sample size: the blocking and tackling of statistics. Anesthesia & Analgesia, 126(2), 691-698.  “Subjects were divided into AP-PCAD with FH (G1)…”5. Abstract, 2nd sentences, “Subjects were divided into AP-CAD with FH (G1)…” �= Thank you very much for the comment. We have corrected the term “AP-CAD” to “AP-PCAD”. = Abstract: .Reviewer #2:1. The authors have addressed my comments. However, I would very strongly recommend one change to the abstract to include the figures for Definite FH. Lines 34-36 should read "The prevalence of Definite, Potential and All FH among AP-PCAD patients were 6%(19/319), 16% (51/319) and 45.5% (145/319) respectively. It is very important to include upfront the figures for definite patients since these are consistent in findings in non-Asian studies and include patients overwhelmingly likely to have an FH-causing variant.= Thank you very much for the recommendation. We have added the prevalence for Definite FH as suggested.= Abstract: .AttachmentResponse to Reviewers.docxSubmitted filename: Click here for additional data file. 18 Aug 2022Familial hypercholesterolaemia and coronary risk factors among patients with angiogram-proven premature coronary artery disease in an Asian cohortPONE-D-21-27710R2Dear Dr. NAWAWI,We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. 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If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.Reviewer #1: All comments have been addressedReviewer #2: All comments have been addressed**********  2. Is the manuscript technically sound, and do the data support the conclusions?  The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: PartlyReviewer #2: Yes**********  3. Has the statistical analysis been performed appropriately and rigorously?   Reviewer #1: YesReviewer #2: Yes**********  4. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.  The Reviewer #1: NoReviewer #2: Yes**********  5. Is the manuscript presented in an intelligible fashion and written in standard English?  PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: Yes**********  6. Review Comments to the Author  Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: This reviewer accepted the responses to my comments from the authors. However, the new information provided in the revised manuscript raises some concerns, as follows:1. The new information provided in the revised manuscript regarding the recruitment does not include group 3. In the Methodology (lines 119-129), it is clearly described that “The inclusion criteria were male and female Malaysians aged ≥18 years, with AP-PCAD and voluntarily consented to participate in this study…” and that “Normal control subjects were collected through community health screening programmes...” Apparently, groups 1 and 2 are subjects with AP-PCAD, and group 4 is normal control subjects (line 132). However, how subjects of group 3, with FH but without PACD/CAD were recruited is not clear.2. CAD includes PCAD, but PCAD does not include whole CAD. The new information in the revised manuscript reads that “G3  and G4 …” (lines 131-133). To make it clear to the readers, in Table 1 the “G3 +FH/-PCAD” would be best abbreviated as “G3 +FH/-CAD”. Similarly, in Table 1, “G4 -FH/-PCAD” would be best abbreviated as “G4 -FH/-CAD”.Reviewer #2: The authors have addressed my comments satisfactorily by including in the abstract the number of subjects with definite familial hypercholesterolaemia**********  7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.If you choose “no”, your identity will remain anonymous but your review may still be made public.Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.  Reviewer #1: NoYes: Professor H.Andrew W NeilReviewer #2: ********** 25 Aug 2022PONE-D-21-27710R2 Familial hypercholesterolaemia and coronary risk factors among patients with angiogram-proven premature coronary artery disease in an Asian cohort Dear Dr. NAWAWI:I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. onepress@plos.org.If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact plosone@plos.org. If we can help with anything else, please email us at Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staffon behalf ofDr. Xiao-Feng Yang Academic EditorPLOS ONE


Background and objectiveThere are three subtypes of low-density lipoprotein (LDL): large buoyant (lb), intermediate, and small dense (sd). Among these LDL subtypes, small dense low-density lipoprotein (sdLDL) has been proven to be an independent risk factor for atherosclerosis. Type 2 diabetes mellitus (T2DM) encompasses several metabolic abnormalities and patients suffering from T2DM without good glycemic control are prone to develop atherosclerosis. Hence, in T2DM, it is recommended to evaluate blood lipids for early detection of hyperlipidemia to identify the risk. A larger percentage of sdLDL in T2DM patients with an optimal or near-optimal LDL level might be a hidden risk factor for atherosclerosis. Hence, we aimed to find the level of sdLDL cholesterol (sdLDL-C) among newly diagnosed T2DM patients with optimal or near-optimal blood lipids and to compare it with age and sex-matched controls.Materials and methodsIn this study, we enrolled newly diagnosed T2DM patients from the diabetic clinic of a tertiary care hospital. The patients were then tested for blood lipids, namely, total cholesterol, triglyceride, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol (LDL-C), including sdLDL-C. Then, age and sex-matched controls with similar baseline lipid levels to the T2DM group (without sdLDL-C) were recruited. After recruitment, both groups were measured for blood lipids including sdLDL-C in a single day. The level of sdLDL-C between the groups was tested statistically by the Mann-Whitney U test.ResultsA total of 50 T2DM patients with a median age of 36 years (Q1-Q3: 33.75-41) were included as the study group and 50 age and sex-matched controls with a median age of 34 years  were recruited. The median fasting glucose was 165 (Q1-Q3: 145-199.25) mg/dL and 90.5 (Q1-Q3: 87.75-95.25) mg/dL (p < 0.0001) in the study and control groups, respectively. The LDL-C was 109.9 (Q1-Q3: 99.4-119.4) mg/dL and 108.5 (Q1-Q3: 87.55-124.1) mg/dL (p = 0.94) in the study and control groups, respectively. The sdLDL-C was 40.11 (Q1-Q3: 36.28-43.58) mg/dL and 24.64 (Q1-Q3: 22-32.49) mg/dL (p < 0.0001) in the study and control groups, respectively.ConclusionNewly diagnosed T2DM patients with blood lipids within an optimum or near-optimum level may have a higher percentage of sdLDL-C when compared with healthy controls. Hence, they may have a higher risk of atherosclerosis and cardiovascular diseases. Clinicians may miss the potential risks if they do not advise the sdLDL-C component of LDL-C while advising for the test for blood lipid. The chronic consequence of type 2 diabetes mellitus (T2DM) is accelerated coronary, cerebral, and peripheral vascular atherosclerosis. When compared to people without diabetes, the death rate from coronary heart disease (CHD) is up to four times greater. Also, major adverse cardiovascular events, apart from mortality, greatly increase healthcare costs . DyslipiLDL has multiple subclasses according to size, density, chemical, and metabolic activity and these properties are responsible for the difference in their atherogenicity. The size and stickiness of large buoyant (lb), intermediate, and small dense (sd) LDL are different . CompareCirculating sdLDL is prone to oxidation, glycation, and desialylation. These modifications heighten atherogenicity. There is a higher affinity of the sdLDL to heparin sulfate proteoglycans in the vessel wall and this increases the penetrability of sdLDL, and after penetration, they enhance the formation of foam cells .Newly diagnosed T2DM patients are commonly screened for the lipid profile and antilipidemic drugs are suggested if the levels are high for the individual . Those wIn this context, we designed this study to find out the level of sdLDL-C in newly diagnosed T2DM patients who are having a normal level of LDL-C. The outcome would help us to know the pattern of sdLDL-C in those patients considered apparently normal according to the level of LDL-C.Type and settingsThis was a cross-sectional observational study where variables were measured in a study group and a control group and compared. Research participants were recruited from the diabetes clinic of a tertiary care hospital. The study was conducted from January 2019 to December 2020.EthicsWe recruited only adult (age > 18 years) patients for this study. All the patients were approached with a brief description of the study aim and procedure and recruited after they voluntarily consented to participate. The Institutional Ethics Committee of Apollo Medical College and Hospital, Hyderabad, India approved this study (AIMSR/IRB/EC/2018/10/075).Minimum sample sizeFor the calculation of sample size, we used our expectations with results from a previous study . We expeRecruitment processPatients who were diagnosed with T2DM by fasting blood sugar (FBS) and glycated hemoglobin HbA1c) measured on two occasions were approached for a detailed history and co-existing disease or ongoing treatment. A thorough clinical examination was conducted by an expert clinician. Those with no apparent co-existing disease or disorder were recruited and tested for blood lipid profile. Participants with an abnormal level of lipids were excluded to get the final pool of research participants. The recruitment process is shown in Figure c measureAfter recruiting the study group, a control group of similar age and sex was recruited from the same tertiary care hospital from the patient’s attendants. They also went through the same procedure of history, clinical examination, and blood tests as the study group.Criteria for inclusionThe diagnosis of T2DM was based on the measurement of fasting blood glucose and HbA1c. If the blood glucose was above 125 mg/dL and HbA1c was above 6.5% on two occasions after a 15 days gap, the patient was diagnosed to be suffering from T2DM . After tBlood testA venous blood sample was collected from the antecubital vein maintaining aseptic precautions after 12-hour fasting. The FBS, HbA1c, and lipid profile were again tested and this result was stored for analysis. The sdLDL-C was measured by quantitative Denka Seiken  assay that quantifies sdLDL-C in blood samples. The test uses a two-step procedure to quantify sdLDL-C. In the first step, using a surfactant and sphingomyelinase, chylomicrons and lipoproteins  are removed. In the second step, a surfactant releases cholesterol solely from sdLDL-C so that it can be measured using conventional techniques .AnthropometryThe research participants were measured for weight, height, and body fat percentage , and body mass index was calculated from the collected data. Single clinicians with previous expertise in anthropometry measured all the parameters. For the measurements of women, a women's attendant was present and prepared the subjects for height and weight measurement. A portable stadiometer  was used to measure the height to the nearest 1 mm. The weight was measured concurrently with the body fat percentage with the Omron Body Composition Monitor HBF-375 . The precautions for body fat measurements were followed before the body fat estimation .Statistical analysisData were checked for distribution by the Shapiro-Wilk test and found not to follow the normal distribution. Hence, data were presented as median and first and third quartile (Q1-Q3) . Mann-WhA total of 50 T2DM patients with a median age of 36 years were included as the study group and 50 age- and sex-matched patients with a median age of 34 years were recruited as control. The age, sex, anthropometric parameters, FBS, and HbA1c level in the study and control groups are shown in Table The blood lipid profile including sdLDL-C in the study and control groups is shown in Table Despite having a similar level of LDL-C , the sdLDL-C was significantly higher  among newly diagnosed T2DM patients.We found that despite having a similar level of LDL-C, patients diagnosed with T2DM had more percentage of sdLDL-C. The underlying reason for this finding may be due to the higher activity of hepatic lipase in a hyperglycemic state . The hepT2DM patients who are first-time diagnosed with the disease may have a high level of blood sugar level for a long period before the diagnosis. The HbA1c indicates a high blood glucose level for approximately the previous two to three months. Hence, in our study, the participants who showed high HbA1c might have an undefined period of hyperglycemia. And that might increase the level of hepatic lipase.According to Hoogeveen et al., sdLDL-C is greater in diabetic individuals compared to nondiabetic patients and strongly correlates with an atherogenic lipid profile. They also reported that although patients with diabetes may have low cardiovascular risk as assessed by the level of LDL-C, sdLDL-C has the potential to predict the risk of coronary heart disease . This isIn a low-risk population, a relationship has been found between LDL-C level and cardiovascular disease mortality in a large cohort with 10 years of follow-up. However, Abdullah et al. concluded that more research is needed to determine if lipid-modifying lifestyle changes and medical interventions improve cardiovascular disease outcomes in low-risk people with increased LDL-C . The curResearch regarding cholesterol and related therapies is evolving. Statin therapy has been heavily marketed for cardiovascular prophylaxis since total cholesterol or LDL-C has been identified as the cause of atherosclerosis and cardiovascular disease. Though it is becoming increasingly clear that the processes are more nuanced and that statin therapy, particularly when used as primary prevention, is questionably beneficial ,22.There are both medicinal and non-medicinal approaches for control of the level of sdLDL-C. There is evidence and ongoing research about the beneficial effect of various nutritional supplements like almonds, avocados, dark chocolate, pistachios, and flaxseeds oil to control sdLDL-C. Exercise may also help in controlling the sdLDL-C level. The current medicinal treatment includes drugs like statins, fibrates, ezetimibe, niacin, and omega-3 fatty acids in various dosage forms. For a comprehensive review, readers may refer to the review by Jin et al. .LimitationsThis study is not a population-based study and was conducted with a sample taken from a tertiary care hospital as a convenience sample with inclusion and exclusion criteria. The duration for which the patients were suffering from T2DM was beyond our capability to measure. The conclusion drawn from the study conducted with a non-probability sample may not be generalized. Hence, the result of this study should be used with caution for clinical decisions.Newly diagnosed T2DM patients with blood lipids within an optimum or near-optimum level may have a higher percentage of sdLDL-C when compared with healthy controls. Hence, they may have a higher risk of atherosclerosis and cardiovascular disease risks despite having an LDL-C level that is considered normal or near-optimal. Hence, the sdLDL-C may be a hidden risk factor among patients otherwise of the "not at risk" category. However, the test for sdLDL-C is still costly for patients in developing countries. Clinicians dealing with patients with T2DM may consider the sdLDL-C level for patients who can afford the test for detecting a potential risk factor for cardiovascular diseases, which is not commonly practiced regularly.


The aim of this study was to evaluate the feasibility and safety of a novel robotic system (KD-SR-01) for partial nephrectomy.Seventeen patients with small renal masses (SRMs) (≤4 cm) underwent KD-SR-01 robotic partial nephrectomy (KD-RPN) from December 2020 to March 2021 in our institution. The operative outcomes and perioperative data, including clinical and histological data, were prospectively collected and analyzed.vs 97.9 ± 10.7 mL/min, p = 0.036). However, no significant difference was observed between the preoperative eGFR and the value on the fourth postoperative day .In total, 10 men and 7 women, with a median age of 51 years, underwent KD-RPN. Four transperitoneal procedures and 13 retroperitoneal procedures were performed without conversion to open or conventional laparoscopic surgery. The docking time and robotic operative time were 3.3 and 68.6 minutes, respectively. The warm ischemia time was 16.9 minutes. No major intraoperative or postoperative complications (Clavien grade ≥III) occurred. The duration of postoperative hospital stay was 5 days. Pathologic examination revealed nine clear cell carcinoma, two papillary cell carcinoma, one oncocytoma, and five angiomyolipoma cases. All surgical margins were negative. The estimated glomerular filtration rate (eGFR) on the first postoperative day was significantly decreased compared with the preoperative eGFR (91.7 ± 12.9 mL/min ® platform are needed to corroborate these findings.KD-RPN was safe and feasible for treatment of SRM. The early oncologic and functional outcomes were promising. Long-term follow-up and well-designed prospective comparative studies with the da Vinci In China, a new robotic platform called KD-SR-01™ , which includes an open surgical console, three robotic arms, and a 3D video imaging system, has been developed. The KD-SR-01 robotic system completed PN in animal experiments. Compared with traditional 3D laparoscopic surgery, KD-SR-01 robotic partial nephrectomy (KD-RPN) showed no significant difference in operation time or other parameters, but the KD-SR-01 robotic system has significant ergonomic advantages.13In recent years, several devices have been under development in Europe and AsiaThe aim of this prospective single-institution study was to evaluate the feasibility and safety of the KD-SR-01 robotic system in a consecutive series of patients undergoing PN.This prospective single-institution study included patients who underwent KD-RPN at the Department of Urology at Peking Union Medical College Hospital (PUMCH), Beijing, China, between December 2020 and March 2021. Our institutional review board approved the study. All patients were informed about the surgical technique and signed a written informed consent form that presented the risk of standard laparoscopic and/or laparotomic conversion. Clinical data of the study population were anonymously collected in an electronic database at the time of recruitment.14 The exclusion criteria were as follows: (1) patients with severe uncontrolled infection; (2) patients with recurrent tumors; (3) patients with a previous upper abdominal surgical history; (4) patients with cardiovascular and cerebrovascular diseases, blood system diseases, and immune system diseases or diabetes, who could not meet the requirements to undergo surgery; and (5) pregnant or lactating women.The inclusion criteria were as follows: (1) 18–75 years old, regardless of sex; (2) indications for PN; (3) TNM tumor stage of T1a; and (4) R.E.N.A.L. score ≤9.Before starting the robotic PN with the KD-SR-01 system, our team consisting of two urologists and two nurses received training for 2 days in a dry laboratory with a third day in a wet laboratory, performing various surgical procedures with this system on pigs. All of the procedures included in this article were performed by members of this highly trained team. In addition, this surgical team has performed more than 500 cases of various operations with the da Vinci system.13The KD-SR-01 system consists of a surgical console, three robotic arms, and a 3D imaging system . The ope® laparoscopic systems were used with 30°, 10-mm, 3D video laparoscopes.Unlike the four-arm system of the da Vinci robotic platform, the patient bed of the KD-SR-01 platform includes a three-arm system . The surKD-SR-01 will be approved for registration  in China in the near future. At present, this research project with KD-SR-01 has passed the inspection of medical devices by the China NMPA and obtained the test report. In 2019, KD-SR-01 passed the NMPA special channel for innovative medical devices and was allowed to enter clinical trial research by NMPA.This study was approved by the ethics committee of our institution.Both retroperitoneal and transperitoneal approaches were administered in our series. The choice of surgical approach was based on the patient and tumor characteristics and surgeon's experience. The retroperitoneal approach was performed in most tumors, including posterior tumors, lateral tumors, and a part of anterior tumors. The transperitoneal approach was performed only in tumors on the medial side of the kidney and a part of anterior tumors close to the renal hilum.After general anesthesia induction, the patient was placed in a lateral flank position. First, a 2-cm incision was made at the midaxillary line 2 cm above the iliac crest, through which the retroperitoneal cavity was created by balloon dilation. After a pneumoperitoneum of 14 mm Hg was established, a 30° 3D video laparoscope was introduced through the first incision. Then, two 10-mm robotic cannulas were placed under direct vision at the anterior and posterior axillary lines ∼2–3 cm above the iliac crest. Another 12-mm trocar was placed for assistance between the camera port and the anterior port .After docking was performed, the standard technique was used to expose the kidney. The renal artery was dissected and exposed, and the kidney was mobilized to expose the tumor . After tThe opened collection system was closed using 3-0 self-barbed sutures. The renal parenchyma was closed with 1-0 self-barbed sutures . Then, tThe patient was placed in a 60° contralateral decubitus position. A 1-cm incision was made at the midclavicular line of the affected side below the costal margin, and a pneumoperitoneum needle was inserted to inject CO2 gas until the pneumoperitoneum pressure reached 14 mmHg. A 12-mm port for the 30° 3D video laparoscope was placed supraumbilically at the outer edge of the rectus abdominis. Two 10-mm robotic cannulae were placed at the first puncture point and at the anterior axillary line below the umbilicus for the robotic instruments.Additionally, 12-mm and 5-mm assistant ports were placed on the midline 5 cm above the umbilicus and 5 cm below the umbilicus, respectively . Then, dThe kidney wound was sutured in the same way as in the retroperitoneal approach . Then, tThe patient variables included age, sex, body mass index (BMI), and preoperative estimated glomerular filtration rate (eGFR); and the operative variables included robotic operative time (ROT), total operative time (TOT), warm ischemia time (WIT), estimated blood loss (EBL), and intraoperative transfusion. The postoperative variables included eGFR on the first postoperative day, eGFR on the fourth postoperative day, postoperative complications within the 30-day follow-up, length of hospital stay, histological characteristics, and surgical margin.14 and categorized as low (4–6) or moderate (7–9).All patients underwent preoperative B-mode ultrasound and enhanced abdominal computed tomography/magnetic resonance imaging to confirm the diagnosis of renal tumors. Tumor complexity was assessed using the R.E.N.A.L. score15ROT was defined as the time from the beginning of the robotic surgical instrument-assisted operation to the removal of robotic surgical instruments. Docking time was defined as the time from moving the surgical system to the operating table until the last cannula was docked into the corresponding surgical arm. Complications were graded using the Clavien-Dindo classification system.The main indicator was the efficiency of the operation, defined as meeting all of the following requirements: (1) the tumor was removed according to the established surgical plan without conversion to RN or open or conventional laparoscopic surgery and (2) the WIT was <30 minutes for patients with an R.E.N.A.L. score of 4–6 and <40 minutes for patients with an R.E.N.A.L. score of 7–9.The SPSS 23.0 statistical software program  was used. The results are expressed as numbers (%) for categorical variables, as the mean ± standard deviation for normally distributed continuous variables, and as medians (ranges) for continuous variables with skewed distribution.2 . The tumors were located in the left kidney in eight cases and the right kidney in nine cases. The median tumor was 3.3 cm . The R.E.N.A.L. score was 4–6 in 12 cases and 7–9 in 5 cases.From December 2020 to March 2021, 17 patients (10 men and 7 women) underwent KD-RPN. The baseline characteristics of the study population are summarized in The intraoperative and postoperative characteristics are summarized in There were no intraoperative complications. Postoperative complications were observed in five patients, requiring the need for antiemetic drugs in three cases and analgesics in two cases. No patients required blood transfusion perioperatively. The median time to discharge was 5 days . Pathologic examination revealed clear cell carcinoma in nine patients (52.9%), papillary cell carcinoma in two patients (11.7%), oncocytoma in one patient (5.8%), and angiomyolipoma in five patients (29.4%). All surgical margins were found to be negative.vs 97.9 ± 10.7 mL/min, p = 0.036). However, no significant difference was observed between the preoperative eGFR and that on the fourth postoperative day .There was a significant decrease in eGFR on the first postoperative day compared with the preoperative eGFR  were observed. Our initial experience suggests that KD-RPN is technically feasible, valid, and safe.13 In another study, Fan and colleagues reported their initial experience with KD-SR-01 robotic pyeloplasty in 16 cases and confirmed its safety and feasibility.16 However, due to the need for fine dissection of renal vessels, complex reconstruction of the renal parenchyma, and a constrained WIT, PN is more challenging than pyeloplasty for both surgeons and the robotic equipment.In a previous study of a porcine model, the KD-SR-01 robotic system showed comparable results with 3D laparoscopic partial nephrectomy (3D-LPN) from an operative perspective, while KD-RPN had advantages over 3D-LPN from an ergonomic perspective.17The KD-SR-01 robotic surgical system offers several unique features not possible in laparoscopic surgery, including a higher degree of freedom with the robotic instruments, motion scaling, and tremor reduction, which enable surgeons to control the surgical arms and instruments more precisely and synchronously in real time. In the present study, the average docking time was 3.3 minutes (2.2–6.3 minutes), which was shorter than that reported in previous literature.The following reasons may contribute to the result. First, the patient cart of KD-SR-01 is a liftable and rotatable suspended operating arm structure platform similar to da Vinci Xi. The movable patient cart can be placed anywhere around the operating table. It is equipped with a laser precise positioning function, which optimizes the docking process and significantly shortens the preoperative preparation time.19 In our experience, clear 3D visualization and good instrument maneuverability account for these results. A previous study reported that the learning curve for da Vinci-assisted PN was 16 cases in terms of TOT and 26 cases in terms of WIT for an experienced renal surgeon with extensive prior experience with LPN.20 Therefore, we believe that once a stable plateau has been reached, KD-RPN might show more favorable results in terms of operative time and WIT.Second, the medical staff attended many training sessions and are experienced in animal experiments, which greatly shortened the learning curve. The average TOT and ROT were 110.5 ± 37.6 minutes and 68.6 ± 26.0 minutes, respectively. The average WIT was 16.9 ± 9.0 minutes, which is comparable with that in previous studies on the da Vinci system.Robot-assisted partial nephrectomy can be performed with the transperitoneal or retroperitoneal approach, and each has its own advantages and drawbacks. The increased working space provided by the transperitoneal approach allowed adequate manipulation space for the devices, thus decreasing external robotic arm conflict. Conversely, the retroperitoneal approach is performed in the small space of the retroperitoneum cavity.21–23However, the retroperitoneal approach enables direct access to the renal artery without the need for mobilization of the colon, which might be advantageous for patients with prior abdominal surgery and for faster recovery of postoperative bowel function. A further potential benefit, which has already been described for the retroperitoneal approach, is that the retroperitoneal space may tamponade hemorrhage and prevent complications caused by the contact of urine with the peritoneum.In our series, KD-RPN procedures were mainly performed using the retroperitoneal approach. In our opinion, even in the small space of the retroperitoneum cavity, the KD-SR-01 system was competent for PN due to its high degree of freedom of the robotic instruments.We have a preliminary understanding of both the advantages and disadvantages of the new platform. First, the open console allows for a natural neck posture, which helps relieve neck pain and stress. Second, the KD-SR-01 system can match the 3D laparoscopic display system of various brands that have been listed, which can greatly reduce the cost. Third, three surgical arms are suspended on the beam of a movable cart, which allows the arms to rotate as a group to adjust to the position of the patient. Fourth, the cart adopts force sensor technology, making it convenient for users to push it. Fifth, a cross-laser device is used to facilitate docking.24 The da Vinci single-port (SP) surgical system has been available for several years, and preliminary data from centers of excellence show surgery with the SP system to be safe and feasible, with perioperative outcomes comparable with traditional multiport robotic surgery.25The lack of tactile feedback is the main drawback of the new platform. In the future, the new robot platform should be developed with a haptic feedback system. In recent years, robot-assisted single-site surgery achieved a better cosmetic effect, lesser pain, and faster recovery than traditional surgery.9 The insertable robotic effector platform was developed at Vanderbilt University, which consists of a 3D telescope and two flexible arms.9However, high-quality comparative studies are currently lacking. In addition to the da Vinci SP system, other single-port platforms are under development and testing. Titan Medical  focused on the SPORT Surgical System as a platform for robotic single-site surgery, which has an open console with 3D HD vision controlling a 3D flexible telescope with fiber-optic-based illumination and two flexible instruments.Development of these new platforms will ideally promote innovation and drive the competitive price pressure downward for single-port technology. Furthermore, long-distance operations based on 5G technology will be the focus of future developments. Despite these shortcomings, the new robot platform might offer a new option for minimally invasive robotic surgery.This study has some limitations. First, in the present study, the team performed 17 KD-RPN procedures, which might be insufficient to reach the stable plateau of the learning curve. Second, to explore the feasibility of KD-RPN, the patients were carefully selected and all candidates had renal tumors with an R.E.N.A.L. score less than 9. Further exploration is needed to assess suitability in more complex cases. Third, in the present study, the surgical team had extensive experience in performing robotic and laparoscopic PN. The learning curve of KD-RPN for surgeons lacking robotic and laparoscopic experience needs further exploration. Fourth, due to the short follow-up period, long-term oncologic and functional outcomes could not be assessed and should be further evaluated after a longer follow-up period.This is the first clinical assessment of the KD-SR-01 robotic surgical system for PN. Our initial experience demonstrated the feasibility and safety of KD-RPN. Despite the relatively small number of patients in our series, the advantages of the new robotic systems are difficult to ignore. Considering the current high costs of da Vinci robotic surgery systems, the emergence of new competitive devices will make robotic surgery more affordable.We further emphasize that such investigations into the feasibility of robot-assisted procedures should initially be performed by surgeons who are experienced in both robotic and laparoscopic techniques to reduce patient morbidity during the learning phase.